SPARC: Unified framework for automatic segmentation, probabilistic atlas construction, registration and clustering of brain MR images

Automated methods for image segmentation, image registration, clustering of images and probabilistic atlas construction are of great interest in medical image analysis. In this work, we propose a model where these different aspects are combined in one comprehensive probabilistic framework. The framework is formulated as an EM optimization algorithm. Validation is performed on simulated and real images in terms of segmentation, clustering and atlas construction. Accurate segmentations are obtained and the different modes in a population of normal controls and Huntington disease patients are discovered. Furthermore, our method reveals the localization of cluster specific morphological differences for each image in the population.